Job Title

Staff MLOps Engineer Were looking for a Staff MLOps Engineer to lead the design, delivery, and evolution of our machine learning platform. In this role you will own the infrastructure and tooling that takes models from experimentation to production building reliable, observable, and scalable ML systems on AWS. You'll work closely with data scientists to productionize models, mentor junior engineers, and champion modern AIpowered development practices across the team. What Youll Do Design and maintain batch and realtime ML inference pipelines for treebased models (XGBoost, LightGBM, CatBoost) and neural networks (PyTorch, TensorFlow) Build and manage CI/CD pipelines for ML model deployment Own infrastructureascode (Terraform) for the ML platform across cloud services Implement observability for ML systems logging, tracing, metrics, drift detection, and alerting Manage experiment tracking and model registry platforms and automate the path from training to staging to production Build and operate feature pipelines and data platform integrations Lead migration to nextgeneration ML compute platforms (e.g., Anyscale), modernizing distributed training and serving infrastructure Partner with data scientists to productionize models translating research prototypes into reliable, monitored services Mentor junior engineers through code reviews, pair programming, and technical guidance; establish best practices and learning paths that raise the bar for the team Champion AIpowered development tools (e.g., Cursor, Claude Code) drive adoption across the team, integrate AI into daily workflows and CI/CD, and evangelize effective usage What You Bring 7+ years in software engineering, MLOps, or platform engineering, with 3+ years focused on production ML systems Deep cloud experience (ideally AWS) Infrastructureascode with Terraform Production ML pipeline experience across both treebased models (XGBoost, LightGBM) and neural networks (PyTorch, TensorFlow), using platforms such as Anyscale, SageMaker, or similar ML experiment tracking and model registry tools (e.g., MLflow, Weights & Biases) Observability for ML systems using Datadog (logs, APM, metrics, anomaly detection) CI/CD with GitHub Actions and AWS CodePipeline Fluency in Python and SQL; familiarity with data platforms (e.g., Snowflake, Databricks) Proven track record mentoring and upleveling junior engineers Experience with AIpowered development tools (e.g., Cursor, Claude Code) and a drive to integrate AI into engineering workflows Nice to Have Experience with distributed training and Raybased compute frameworks Background in financial services, fintech, or other regulated industries Contributions to opensource MLOps or infrastructure tooling Familiarity with model governance, audit trails, and compliance requirements for ML in production Benefits Flexible health benefits & life insurance 21 days PTO + statutory holidays, and personal leave Health & personal spending accounts Wide variety of discounts through our partner network Access to early use of products and discounts on fixedterm Neo mortgages Parental topup & equity vesting during longterm leave Neo night events and companywide huddles for education Ownership structure that enables you to share in our path to victory Shortterm incentive plans (STIP) for high performance Collaboration with bright minds in Canadas leading fintech ecosystem Equal Opportunity & Security Screening We believe in equal opportunity and are committed to creating an inclusive climate where everyone can thrive. Successful candidates for this position will be required to undergo a security screening, including a criminal records check and a credit check. Data Privacy Notice By continuing with your application, you agree to the Candidate Privacy Notice, which guides how we process your personal information for the purpose of your application. Neo Financial leverages artificial intelligence (AI) to support our recruitment process, but all final hiring decisions are made by humans. We are hiring for an open, vacant position. #J-18808-Ljbffr